1. Introduction ZJU, China and around the world

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1. Introduction Bioinformatics – Biological Big Data

陈铭（[email protected]）

2015年9月14日

Bioinformatics

生物信息学 Question to you!

What is Bioinformatics？

How about bioinformatics research in ZJU, China and around the world?

What are the current hot topics and future directions？

How can you be a bioinformatian？

Puzzle for math & bio

ScienceDaily (June 19, 2008)

The Wheel of Biological Understanding

http://www.cyberorissa.com/

Top-down approach

Bottom-up approach

Two ways of looking a biological problem

Life‘s Complexity Pyramid (Oltvai-Barabasi, Science 10/25/02)

Biological Complexity In Escherichia coli, for instance, there are 225,000 proteins,

15,000 ribosomes, 170,000 tRNA-molecules, 15,000,000 small organic molecules and 25,000,000 ions inside the a few µm cell.

There are estimated 1014-1016 biochemical reactions in a cell.

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Eukaryotic Genome Complexity

http://www.whfreeman.com/

中心法则

Francis Crick, 1958; Nature 227 ,

1970

93%

3-5%

ncRNA (75% plants)

视频：life

转录因子

生态

个体

组织/器官

生理学

生化遗传

分子结构基因序列生化反应基因表达

Complex systems of

simple elements have

functions that emerge

from the properties of the

networks they form.

Biological systems have

functions that rely on a

combination of the

network and the specific

elements involved.

Biological Systems Subdisciplines of biology

Biochemistry 生物化学examines the rudimentary chemistry of life;

Molecular biology 分子生物学studies the complex interactions of systems of biological molecules;

Cellular biology 细胞生物学examines the basic building block of all life, the cell;

Physiology 生理学examines the physical and chemical functions of the tissues, organs, and organ systems of an organism;

and Ecology 生态学examines how various organisms interact and associate with their environment.

生物信息学大事记(一)

计算机科学年份生命科学

Blaise Pascal: mechanical calculators 1642

Telegraph 1858

1859 Darwin’s Origin of Species

1865 Mendel’s peas

1869 DNA first isolated

Telephone 1876

1879 Mitosis observed

1900 Rediscovery of Mendel’s work

1902 Orderly inheritance of disease observed Chromosome theory of heredity

1909 The word gene coined

1911 Fruit flies illuminate the chromosome theory

1941 One gene, one enzyme

第一台电子管计算机ENIAC诞生 1943 x-ray diffraction of DNA

1944 DNA is “transforming principle” Jumping genes

The first Computer Bug 1945

Grace Murray Hopper: first compiler 1952 Genes are made of DNA

1953 Francis Crick，James Watson和Maurice Wilkins发现DNA的双螺旋结构

1955 第一个蛋白质序列(牛胰岛素)被测定

1956 “生物学中的信息理论讨论会”于美国田纳西州的Gatlinburg召开

生物信息学大事记(二)


中国第一台电子管计算机诞生 1958 由Hubert P.Yockey编辑的《生物学中的信息理论讨论会》出版

Telephone calls switched by computer, COBOL 1960

Robert Berner: ASCII, computer mouse 1963

Thomas Kurtz: BASIC 1964

1965 中国人工合成牛胰岛素结晶

1968 First restriction enzymes described

Kenneth Thompson开发UNIX操作系统; Arpanet,

Internet predecessor; the first computer hacker

1969

Needleman-Wunsch序列比准算法 1970

Ray Tomlinson wrote The first email program on Arpanet; the first personal computer

1971

Dennis Ritchie发明C语言; NCSA developed Telnet 1972 First recombinant DNA

FTP 1973 First animal gene cloned

Bill Gates和Paul Allen成立微软; Bill Joy developed

C shell (csh) and Vi text editor

1975 75-77:DNA sequencing

David Boggs invent Ethernet; Stephen Wozniak et al found Apple Computer.

1976 First genentic engineering company

Ward Christensen started The first computerized bulletin board system (CBBS). TCP split into TCP and IP

1978

Usenet born; Brian Kernighan published C program language. Apple Computer introduced Apple II+

1979

First computer virus, DNS is conceived by David Mills; Smith-Waterman序列比准算法, MS-DOS

1981 中国实现酵母内氨酸转移核糖核酸的人工合成

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生物信息学大事记(三)


Andreas von Bechtolsheim etal found Sun Microsystems; GNU by Richard Stallman. SMTP is published.

1982

Korn shell (ksh) relased by David Korn 1983

The X window system is released by Robert W. Scheifler; Apple introduce macintosh System 1.0

1984

Bjarne Stroustrup创建C++语言；Apple introduce

macintosh System 2.0 视窗微软问世 windows 1.0

1985 Kary.Mullis创立PCR技术；生物信息学专业期刊(CABIOS)

创刊；德国生物信息学会议(GCB)举行；

Apple introduce macintosh System 3.0 1986 日本核酸序列数据库DDBJ诞生；蛋白质数据库SWISS-PROT建立;中国开始实施高技术研究发展的

“８６３计划”

Larry Wall推出Perl语言 Apple introduce macintosh System 4.0; Windows 2.0

1987

Compact Disk Recordable (CD-R); Pearson实现FASTA程序 Apple introduce macintosh System 6.0

1988 美国国家生物技术信息中心（NCBI）成立；

MPEG audio Layer III (MP3) patent; the JPEG standard is adopted; Tim Berners-Lee, WWW protocol

1989

Altschul实现BLAST程序；HTTP 1.0 标准发布;

Arpanet ceases to exist (INTERNET). Archie by Alan Emtage created.

1990 国际人类基因组计划(HGP)启动；第一届国际电泳、超

级计算和人类基因组会议在美国佛罗里达州会议中心举行；

Gopher by Paul Lindner. Python by Guido van Rossum; Tim Berners-Lee announce the WWW project; Linus Torvalds releases Linux versions 0.01.

Sun Microsystems release Solaris1.0 Apple introduce macintosh System 7.0

1991

Mosaic web browser 1.0 released. CERN announced WWW would be free to anyone.

Microsoft windows NT3.1;FreeBSD version 1.0 relaeased

1993 欧洲生物信息学研究所（EBI）获准成立；第一届

ISMB国际会议美国国家医学图书馆(NLM)举行；HGP新5年计划;中国开始参与人类基因组计划

生物信息学大事记(四)


James Gosling推出JAVA语言 Opera web browser released. David Filo and Jerry Yang

start their guide, later yahoo.com First spam messages is posted. Netscape web browser released. Linux kernel 1.0 The first alpha version of Ruby relased by Yukihiro Matsumoto

1994 Marc Wilkins提出蛋白质组(Proteome)的概念；细菌基因组计划

Sun launches Java.

Apache web server 0.6.2 released Tatu Ylonen announces the SSH

Internet explorer 1.0 released Microsoft rease Windows 95

1995 人类基因组物理图谱完成

日本信息生物学中心（CIB）成立

Larry Page and Sergey Brin, search engine BackRub, later Google. POP3 is published. W3C推出XML工作草案.

Microsoft release windows NT4.0 Linux kernel 2.0; OpenBSD2.0

1996 Affymetrix生产商用DNA芯片北京大学蛋白质工程和植物遗传学工程国家实验室加入欧洲分子生物学

网络（EMBnet）

DVD format released Mac OS 8 released

1997 大肠杆菌基因组完成

北京大学生物信息学中心(CBI)成立；中国科学院召开

“DNA芯片的现状与未来”和“生物信息学” 香山会议

CIH virus by Chen Ing-Hou, first known virus to target the flash BIOS

Windows 98

1998 亚太生物信息学网络（APBioNet）成立；瑞士生物信息学研究所（SIB）成立；美国Celera遗传公司成立；线虫基因组完成；CABIOS期刊更名为Bioinformatics

中国人类基因组研究北方中心（北京）和南方中心（上海）成立线虫基因组完成

Apple introduce Mac OS 9 and Mac OS X Server Linux kernel 2.2

1999 人类22号染色体序列完成中国获准加入人类基因组计划，成为第六个国际人类基因组计划参与国

生物信息学大事记(五) 计算机科学年份生命科学

Windows 2000 2000 德、日等国科学家宣布基本完成人体第21对染色体的测序工作

果蝇基因组完成中国科学院上海生命科学研究院生物信息中心(SIBI)成

立

Windows XP Linux kernel 2.4

2001 美、日、德、法、英、中６国科学家和美国Celera公司联合公布人类基因组图谱及初步分析结果

首届全国生物信息学会议(CCB)举行；中国完成籼稻基因组工作框架图

2002 老鼠基因组完成

Windows Server 2003, Sony Blu-Ray DVD, DragonFly BSD project announced. Linux kernel 2.6

2003 HGP完成

IBM’s Blue gene/L super computer. Internet speed

record broken 7.57gb/s. Pioneer announce optical drives to store 500GB of data. Optical network speed record broken.101gb/s

2004 Proteomics: Decoding the Genome

NGS

2005 黑猩猩、狗基因组测序完成

中德计算生物所成立

2006 Paleogenomics: digging out fossil DNA

PiRNA

谷歌和IBM 合作推动云计算 2007 Human Genetic Variation

英特尔发布酷睿i７处理器 2008 千人基因组测序计划启动；拟南芥１００１株系测序启动

我国“天河一号”超级计算机以每秒２５７０万亿次 2010 外显子测序

作业1

Key development in the past 5 years

Biology

Computer science

Information technology

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What Technology Do We Have

For Big Data ??

字节数 Byte

Kilobyte (KB) 103 =210

Megabyte (MB) 106 =220

Gigabyte (GB) 109 =230

Terabyte (TB) 1012 =240

Petabyte (PB) 1015 =250

Exabyte (EB) 1018 =260 人类文明开始至2003年：5ET

Zettabyte (ZB) 1021 =270 2012年2.7ZT

Yottabyte (YB) 1024 =280

EBI stores 20 petabytes

CERN generates 15 PB every year!

http://www.google.com.hk/url?sa=i&rct=j&q=how+big+terabyte+exabyte&source=images&cd=&docid=w9vc7Qhx0szEiM&tbnid=ror6quTqk44iRM:&ved=&url=%68%74%74%70%3a%2f%2f%73%65%72%61%64%69%67%6d%2e%63%6f%2e%6e%7a%2f%63%61%74%65%67%6f%72%79%2f%6f%70%65%6e%64%61%74%61&ei=1itSU4q2PK6tiQe804DgBg&psig=AFQjCNHxSl-c-akH6tiexYNsZEC_Ms2TrA&ust=1397980503467960

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Genetics & Genomics

Genomic achievements since HGP

Nature 2011, 470: 204–213

Omics to Systems Biology

Genomics

Proteomics

Systems Biology

Transcriptomics

Metabolomics

Phenomics

1990 1995 2000 2005 2010 2015 2020

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新一代基因测序仪和功能基因组学

Ion Proton NextSeq 500 HiSeq 2500

新一代测序平台的出现为转录组和基因组测序提供了非常好的机遇，不论是在测序价格上还是在精度上都具有很高的可选择性。

比如，通过对作物在冷驯化或干旱适应或盐胁迫等逆境条件下的不同阶段上进行转录组测序，从而更好全面的检测作物在转录组水平上是如何应对极端环境。

MiSeq Ion PGM

HiSeq X Ten

• cost $10 millions

• 125 bp read length

• $1000 per genome

• cost $900

• 80 kb read length

MinION

Mapping 24K genes (1990-2001)

Mapping 10-15M SNPs (2002-2008)

Sequencing the personal (2008)

Personal Genome Project (2011)

1 Billion $ /(2004) 20 Billion $ (2001) 1 Million $ (2008) 0.1 Million $ (2011)

Every 10-12 month： • Data doubled • Seq cost half

Personal Genome and data ￥200/exome (2020)? End of 2020, 90Million Chinese to be genome sequenced!

Biomedical big data for personalized medicine

Year 2020 In China, Heathcare 2000yuan/person Biomedical data ~EB（=1000PB） Personal genomic sequencing becomes routine

Economy Research

Person

$1

00

0美

金/全基

因组

(2

01

4)

中国地区已经成为继北美和欧洲之后的第3大二代测序仪器设备拥有区，图中标注的数字为二代测序仪器数目，其中可以看出中国的二代测序仪器主要分布在深圳、北京和上海地区。

二代测序仪器的世界分布图

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全球测序项目能力预测

个人测序

每个物种测序，100M

基因组大数据商业化前景解决基因组医学的商业应用瓶颈问题

传统医学：回顾式、经验性、封闭式、不确定性

医学2.0：预防性、个性化、预测性、开放性

Human Genome:

$2.7 Billion, 13 Years

Human Genome:

$900, 6 Hours

2012:

Oxford Nanopore

MiniION

2003:

ABI 3730 Sequencer

The Problem of Big Data in Biology

A decade’s progress

“BGI, based in China, is the

world’s largest genomics

research institute, with 167

DNA sequencers producing

the equivalent of 2,000

human genomes a day.

BGI churns out so much

data that it often cannot

transmit its results to clients

or collaborators over the

Internet or other

communications lines

because that would take

weeks. Instead, it sends

computer disks containing

the data, via FedEx.”



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生物学面临的大数据挑战自人类基因组计划完成以来，以美国为代表，世界主要

发达国家纷纷启动了生命科学基础研究计划，如国际千人基因组计划、DNA百科全书计划、英国十万人基因组计划等。这些计划引领生物数据呈爆炸式增长，目前每年全球产生的生物数据总量已达EB级，生命科学领域正在爆发一次数据革命，生命科学某种程度上已经成为大数据科学。

英国医学研究理事会（MRC）

“医学生物信息学计划”

生物信息学

Biology + Informatics = Bioinformatics

But

1 + 1 =/= 2

生物信息学是生物科学与信息科学的交叉学科，是利用计算机科学（信息学）的技术手段来研究生物学的数据，如对生物数据进行获取(retrival)，存储(storage)，传输(transfer)，计

算(manuipulation)，分析(analysis)，模拟(simulation)，预测(prediction)等等的一门新兴学科，

是21世纪科学发展的热点之一。

Biology, Bioinformatics, Systems Biology

Experiment

Information Technology

Computation

Hardware & instrumentation Mathematical & Physical Models

DNA Sequence

Gene & genome organization

Molecular evolution

Protein structure, folding, function & interaction

Metabolic pathways regulation

Signaling

Networks

Physiology & cell biology

Interspecies interaction

Ecology & environment

基因组测序

Genome sequencing 基因组数据分析

Genomic data analysis

统计遗传学

Statistical genetics

蛋白质结构预测、折叠、设计

Protein structure prediction, protein dynamics, protein folding and design

蛋白质组学

Proteomics 功能基因组学（生物芯片等） Functional genomics (microarrays, 2D-PAGE, etc.)

高科技野外生态学

High-tech field ecology

数据格式、标准化及分析复杂生物数据工具 Data standards, data representations, and analytical tools for complex biological data

动态系统建模 Dynamical system modelling

计算生态学

Computational ecology

Bioinformatics

代谢组学 metabolomics

陈铭：整合生物信息学（2006）

转录组学 Transcriptomics

表型组学Phenomics

Post-genomic era

Sequence Structure Function

研究对象

Molecular & Cellular Biology分子与细胞生物学

BioPhysics生物物理学

Brain&NeuroSci脑和神经科学

Medicine&Pharmaceutics医药学

Agriculture农牧渔林学

Molecular&Ecological Evolution分子和生态进化

…

陈铭，后基因组时代的生物信息学，《生物信息学》，2004

http://bd2k.nih.gov/index.html

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研究内容

Database数据库建设

Data Mining & Integration数据库整合和数据挖掘

Sequence Analysis序列分析

Structural Analysis & Functional Prediction结构分析与功能预测

Large Scale Expressional Profile Analysis大规模功能表达谱的分析

Modeling and Simulation of BioPathways代谢网络建模分析

Reconstruction预测调控网络

Network Analysis网络普遍性分析

Modeling模型分析

Program Development程序开发

Commercialization商业化


Bioinformatics













Bioinformatics













Roche 454 Illumina HiSeq 2000 ABI SOLiD

Bioinformatics













Bioinformatics













Bioinformatics













http://upload.wikimedia.org/wikipedia/commons/4/43/Genome_viewer_screenshot_small.png

http://upload.wikimedia.org/wikipedia/commons/2/29/Signal_transduction_v1.png

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How to Make Sense of the Data?

RxList

DrugBank

BRENDA

GenBank

GeneCard

OMIM

EMBL

BioBase

ExPASy

KEGG

PDB

...

How can we exploit them to reveal

the mechanisms of life?...

^^n knowledge

1k+ databases

N tools

Seq-robot

HPLC

NMR

X-ray

...

BIG DATA

整合生物学

Phenotyping

data

整合生物信息学

1. 整合生物信息学的研究领域

2. 生物数据挖掘与整合

3. 生命科学与生信技术的整合

4. 学科、人才的整合

陈铭，整合生物信息学，《计算机教育》，2006

Core Laboratory Facility:

Data Generation

Core Computational Facility:

Data Processing, Storage,

and Dissemination

Cyber-infrastructure, Data Management, Data Analysis Pipeline, and Data Display

(1) LIMS for raw data & protocol

(2) Preprocessed data management

(3) High performance computing

(4) Data validation and integration

(5) Knowledge representation

Data Mining and Knowledge Discovery

Bioinformatics

Computing Biological Complexity

http://redpoll.pharmacy.ualberta.ca/drugbank/index.html

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM

http://www.genecards.org/index.shtml

http://www.brenda.uni-koeln.de/index.php4

http://www.ncbi.nlm.nih.gov/

http://www.rxlist.com/script/main/hp.asp



http://images.google.cn/imgres?imgurl=https://www.preventpeerpressure.com/BanneAds/RXlist.gif&imgrefurl=https://www.preventpeerpressure.com/resources.htm&usg=__HcqJ5rtv6rqSaq6ONflmn2bZst0=&h=81&w=197&sz=7&hl=zh-CN&start=3&um=1&tbnid=CoHlbBJi8GsM5M:&tbnh=43&tbnw=104&prev=/images%3Fq%3DRxList%26hl%3Dzh-CN%26sa%3DN%26um%3D1%26newwindow%3D1

http://www.rcsb.org/pdb

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Current Subfields in Computational Systems Biology 10 Useful Bioinformatics Skills to Have

Bioinformatics is a highly specialized, technical field. You need a background in both biology and in information management, as well as specialized skills specific to the field of bioinformatics. Here are ten of those skills that it’s good to have.

10 Useful Bioinformatics Skills to Have

1. Good communications skills. As a

bioinformatics specialist, you will be communicating complex data to people with a variety of backgrounds. It’s very much like being a translator. You have to know the languages involved, and you have to be an expert communicator in order to help people understand each other.


2. Good teamwork skills. Bioinformatics

is not for lone rangers. Researchers can sometimes work independently, but bioinformatics is about information and communication. You will be working on a team with people who have diverse backgrounds and differing areas of expertise. Good teamwork skills are essential.


3. The ability to multitask. You will

need to be able to handle several complex tasks at a time. This can be a high pressure job with deadlines that have to be met. The ability to multitask will help you manage your job with less stress.


4. Flexibility. You may be moved from

one project to another as your skills are needed. You may have to put aside a project you are working on to help someone with an urgent request. You may need to stop what you are doing and explain a computer model to a scientist. Flexibility is a key skill to have in bioinformatics.

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5. A working knowledge of biology and its applications. You don’t have to

be an expert in biology, but you do need to know what kind of information you are working with. It is especially useful to know about molecular biology and genetics and to understand recent genetic research.


6. Proficiency in computer languages. You need to know basic programming languages like JAVA and HTML, SQL and PERL. Most bioinformatics programming utilizes PERL.


7. Skill in data mining. Being able to

extract data from multiple resources is invaluable.


8. Good data visualization skills. You’ll

need to be able to take complex data and interpret it into models and other ways that make it understandable for biologists and other team members.


9. Experience with bioinformatics tools, such as Blast, BLAT, sequence

analysis algorithms and clustering tools.


10. Experience in using bioinformatics resources, such as the UCSC genome

browser and Entrez. You’ll need to be familiar with the National Center for Bioinformatics (NCBI) and the database and analysis tools available on their website.

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Bio-programming

Computer

Internet

Web programing: HTML, XHTML, XML, SVG, XSL/XSLT, XQL, Java Script, CSS, Apache, IIS, CGI, asp, php, etc.

Perl, Java, C++, Python, SQL, mySQL, etc.

Open Source

Bioperl, Biojava, BioC++…

Keywords

Database

Web-based

Parallel/grid/cloud computing

Image analysis

modeling

Artificial intelligence

Data mining

……

Data Mining

用得比较多的数据挖掘的技术方法：机器学习（归纳逻辑程序（Inductive Logic Programming），遗传算法（Genetic Algorithm），神经网络（Neural Network），统计方法（Statistical Methods），贝叶斯方法（Bayesian Methods），决策树（Decision Tree）和隐马尔可夫模型（Hidden Markov Model）等等），文本挖掘，网络挖掘

陈铭,生物信息学,2007

现状

美国

欧盟

德国

英国

其他

日本

中国

俄罗斯等

International Conference on Intelligent Systems for Molecular Biology (ISMB)

European Conference on Computational Biology (ECCB)

International Conference on Research in Computational Molecular Biology (RECOMB)

Workshop on Algorithms in Bioinformatics (WABI)

Pacific Symposium on Biocomputing (PSB)

International Conference on Systems Biology (ICSB)

Integrative Bioinformatics Workshop

内蒙古大学，罗辽复中科院生物物理所，陈润生

天津大学，张春霆

现状?

CBI:the Centre of BioInformatics at Peking University，罗静初

BioSino:中国科学院上海生命科学研究院生物信息中心，陈渃南、李亦学

BGI: 华大基因，杨焕明

复旦大学，郝柏林

中科院，赵国屏

中德计算生物所

浙江大学

清华大学，孙之荣、张学工

生物信息学专业

浙江大学、北京大学、中国农业大学、南开大学、南京大学、中国科学技术大学、山东大学、中国科学院研究生院、清华大学、国防科学技术大学、上海交通大学、华中科技大学、南京林业大学、中南大学、中国药科大学

复旦大学、中山大学、云南大学、四川大学、东北大学、东南大学、暨南大学、重庆医科大学北京师范大学、第三军医大学

吉林大学、上海大学、南京农业大学、西北农林科技大学、军事医学科学院

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培养目标

本专业培养具有生物信息学基础理论、基本知识和科研技能，能在有关研究单位、高校或企事业单位从事生物信息学领域的科研、开发或教学工作的高级科学技术人才，并为生命科学、计算机科学等相关交叉学科输送研究生后备力量。

专业知识与能力

本专业（理学学士）学生的培养，重在双语教学，强化数学和计算机的基础，拓宽知识面，扎实现代生命科学基本知识的基础上，对学生进行生物信息学、生物学数据库技术、基因组学、蛋白质组学、分子遗传与进化、系统生物学和基因芯片数据分析等方面的基础理论、基础知识和基本科研技能的专业培养与训练。

专业课程

生物化学、分子生物学、Linux应用技术基础、计算机网络应用技术、生物信息学、生物学数据库及实验、序列与基因组分析、蛋白质组学分析、系统生物学、生物芯片原理及数据分析等

分子遗传与分子进化、生物数据挖掘与知识发现、计算生物学导论、计算机辅助药物设计、生物代谢网络建模等

毕业情况

本专业具有良好的教学、科研与商业就业前景，80%以上的毕业生将继续读研或出国深造；

其余毕业生可在生物信息及其相关领域的科研机构和大专院校从事研究、开发、教学和管理工作。

900801

Biomedical

Biofood-products

Biomaterial

Bioagriculture

Bioresurces

Bioenvironmental

Bioelectronics

Bioindustrial Process

Potential Biotech Industries

Nature Biotechnology 18, 1247 - 1249 (2000)

The changing marketplace of bioinformatics

2015/9/21

14

Source: Genome Technology, 2001.02.01

Belgium

2%

Germany

21

(16%)

US

84

(64%)

France

5%

Netherlands

1% UK

10

(7%)

Canada

3%

Israel

1%

Sweden

1%

Global Bioinformatics Industry

Practice

Quiz (10%)

Exam (60%)

Homepage (30%) Apache httpd server HTML Sequence analysis

http://www.cls.zju.edu.cn/binfo/members/G_photo/2013.jpg

Documents

1. Introduction ZJU, China and around the world